{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 均匀分布（Uniform distribution）\n",
    "***\n",
    "## 定义\n",
    "\n",
    "对于投骰子来说，结果是1到6。得到任何一个结果的概率是相等的，这就是均匀分布的基础。与伯努利分布不同，均匀分布的所有可能结果的n个数也是相等的。\n",
    "\n",
    "如果变量X是均匀分布的，则密度函数可以表示为：\n",
    "\n",
    "<img src=\"./img/7.png\" style=\"width:400px;height:300px;float:left\"> "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "你可以看到，均匀分布曲线的形状是一个矩形，这也是均匀分布又称为矩形分布的原因。其中，a和b是参数。\n",
    "\n",
    "花店每天销售的花束数量是均匀分布的，最多为40，最少为10。我们来计算一下日销售量在15到30之间的概率。\n",
    "\n",
    "日销售量在15到30之间的概率为(30-15)*(1/(40-10)) = 0.5\n",
    "\n",
    "同样地，日销售量大于20的概率为 = 0.667"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(-5,1.25,'Nniform Distribution - Overview')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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wYrRoTmViisq79anXZri6N5WUAACEFG7JAAAAEDGMquei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\ndsd4omWhF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      "text/plain": [
       "<matplotlib.figure.Figure at 0x202ee643b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# IMPORTS\n",
    "import numpy as np\n",
    "import scipy.stats as stats\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.style as style\n",
    "from IPython.core.display import HTML\n",
    "\n",
    "# PLOTTING CONFIG\n",
    "%matplotlib inline\n",
    "style.use('fivethirtyeight')\n",
    "plt.rcParams[\"figure.figsize\"] = (14, 7)\n",
    "plt.figure(dpi=100)\n",
    "\n",
    "# PDF\n",
    "plt.plot(np.linspace(-4, 4, 100), \n",
    "         stats.uniform.pdf(np.linspace(-4, 4, 100)) \n",
    "        )\n",
    "plt.fill_between(np.linspace(-4, 4, 100),\n",
    "                 stats.uniform.pdf(np.linspace(-4, 4, 100)),\n",
    "                 alpha=.15)\n",
    "# CDF\n",
    "plt.plot(np.linspace(-4, 4, 100), \n",
    "         stats.uniform.cdf(np.linspace(-4, 4, 100)),\n",
    "        )\n",
    "\n",
    "# LEGEND\n",
    "plt.text(x=-1.5, y=.7, s=\"pdf (normed)\", rotation=65, alpha=.75, weight=\"bold\", color=\"#008fd5\")\n",
    "plt.text(x=-.4, y=.5, s=\"cdf\", rotation=55, alpha=.75, weight=\"bold\", color=\"#fc4f30\")\n",
    "\n",
    "# TICKS\n",
    "plt.tick_params(axis = 'both', which = 'major', labelsize = 18)\n",
    "plt.axhline(y = 0, color = 'black', linewidth = 1.3, alpha = .7)\n",
    "\n",
    "# TITLE\n",
    "plt.text(x = -5, y = 1.25, s = \"Nniform Distribution - Overview\",\n",
    "               fontsize = 26, weight = 'bold', alpha = .75)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(-5,1.1,'Nniform Distribution - loc and scale')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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3a9fOeNyJ+3Jzc9WiRQuf7n/06NHKycnR5MmT9dZbb+mt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\nEmDAhBoU0iAi56lkWucKDgP8w4EpAK7rSLGjK+RsPqZ/PKb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52+JF\nqlcEVg8CG6IisErGdtUrAsuBb/jUo5jxUaKb78Kt2ZRMA25px7e04wFWrr/Kn/gdVKsI1NFgERGR\nBUVBoIhMBti7AAAgAElEQVSIyDyqHP/0cZ54eA++cBbbfh1B60ZsbjmZrX+Amx6aCQhVDVjfKtWA\nb42UeOZUgZQ1nCs40oFhcCKi5GBd28J7+1YtCGypdTQ4nb3W25l31Y4Gl65mRWC5GtAMHSPo3w82\nwExPQCqFGTkLcYTv6r2Kn/DS+MzFr63JqyJQRERkIVl47yRFREQaSOU4sJs6Tjz8PG5ykJQNCFo3\nzoR+tql31nqFgI3g6weT8GRLR4rrO0OmIsc/D+Z58UyJXT1p/uXm3IKaGl2ML76t2TVuRWC1o8Gx\nN+Wg9yp+npd+CoBbugK3bBUUCwRv7MEOHsat3kB0670zlYNzQhWBIiIiC55+mhAREZln3hVxE4dw\nU+XJwJ03z/OOZD5UqgEHJyKeOVXAGsP2JSHr2gL2jUQ8d6rIwHiENeeHyywU0eUcDW6AHoHVjgZD\n9V6Kl61SDThyNqkGNBa3fDV+yVLsqePYgYPYc6eTScHGJMNE5kj1HoEKAkVERBYSBYEiIiLzpBLk\n+Okh3MRh8I6gfQu2aVn5yLC+TTeifzyUVANuaEvxnu40kYMXz5Q4NpmU3f3KmqRJ4MKJAav3v8vV\nGhbSoBWBAMWr+KKlXnoaANfdS7xyPTiHHTyEHT0LQHTDrmThXAbGVSoCTTGfhJciIiKyIOgnDBER\nkXmSVHXFuPH9uPEDAKR67yvfu5BiHrnWKtWAw/mYx44lFVTbl4RsbE9xYCzileEiAA+szNKRsTPr\nFwoNC7lQaKr///ddVwTOTAoeJ9i3N7mpbw2+ZxnmzAns8QEA4i03Qq75/Po54qsdDQYoVb8WRERE\nZO4pCBQREZlPrgRBFozF5pZjW9YC6gXYqB4+klQDrmlNcXN3SGBgz5kiB8eSasCPr8/N5/ZqqhoE\n1uoRWCssqiOpWkeDr1K+n9r7DACuswe3aj0YSzB4GHvmJADRjXdcnU90uWq8tjoeLCIisnBoWIiI\niMgcqAz+8MURvI+wmW4ATJAl6NiOCdsx5du8jzEmmM/tyhzy5eq+6cjz7f4kMLm+M2RLR8jhsZi9\nZ0t477mtN8OK5mDBVQNC9aPBjV0RWP32an9Pl8z7pLqvVCT16vMAuL7VuKXLMcOnsMf7AU+8ZjO+\nY8mcVwPCO1QEKggUERFZMBQEioiIzIkkGSgdfQRfPEdq2X3Y9usxNoUJWwk6rp/pGagQsLE4D4GB\nb/dPEztPX3PA/8/enQfJVd93v//8zunTM9MzI40WNBJaQBIWIAtsvIDBIQIHJTcJfhyLJza4XJTv\nLWNuUo6J7+NyXUjdSjmuhCSuhLhIXSfxEhdPuHLZsaM4zgoEK9gPxsYWBgyIxUgjoWEkoW327j7n\nd//o6dHM9O9IPYu6e87v/aqiGHWfbg6aI033p7/L21ZGag+lnxwr6qVTZUnSBzd3NPlM082mNdjn\nGYHzag22VjJG4bM/kmwiu2S5knUbpVyk4ODPZY70S5LKb3v3PP4j85RaETjKsAMAAFoEQSAAAOdZ\ntRowGe5TfOp5yYSypUGZIKdk7KiUlBQULpRpsSovNEYYVDYAf+3lEUnStmWRti6PdGg41tPHSyol\nVtuWR3rT0miyerDVuAKuLo9bg1O3Bs8nDQsCyVrlfvx9SVKyZr2SNetlTr6h4PABmaSsZM0G2QvW\nnKkebDAqAgEAaH0MIAIAoEHKr/+nJCno3KCga6NsPKb42BMqHfiaSq/9y2RFIPzz9PGSYistbw90\n5YpI3VGgp94o6cWJasAPbK7MBnQU3rUEV0XgkqQ2/LEmkA2z/zl0WmvwfJeFBIcPyNhEttCl+MKL\npLYOBa/tV3D0sCSpfNV1lQOb9XdJWkXg2GiDTwQAAKTJ/isxAACaaLIacOzoRDWgUdC9SaZjjZLB\nV5ScfkHJ2FEFS7dObBG2VAZ6aENXTndd0aVSIl21Mq+BkVg/OlLUSCnRpiU5XbUyL6lSPdiKinFt\n8OSqCEzybZIH13daa3BxnvlcsmylStt/XYpjJes2yQyeVND3kkxxXMmKXiXrNlUObEI1oERFIAAA\niwFBIAAADVAeeFSSFBTWKuzeItlYyeCLldZgSbkLqnO9rKrzBOGPZW2B3rO2XaXEKgqMXh+pVAhK\n0s6NldmAcWJbNggsOwKuLseMQB8WhUhSFLgTv/I8KwJV6FK85QopLkthTho4ITNRjVl+y7sqxzRh\nScgktgYDANDyCAIBADhPJjcFl04rfuPHkqSga5NMYZ3syCElg69IksIV75CJuiePhz+eO1FSR2i0\nqiNQZxQomgj6NnbntHNjh96+MtL2C9sltW41oOSuCOx0VATaKN+I02m61IrAOQaB5vWDUpSX7V4q\n5dsrIaAku6JX5bdcI7N+k5JL3lw5uFkhoM5WEUhrMAAArYIgEACA86w88F+SpKCjV8GSLZIJFA++\nqGS0Mtcr13tDE88OjZZMLPz48dGi/uq5IZ0cT/Teizu0c2OHuia2TORDo7dfkNdVKyNJavmWcdfs\nO9fWYB8WhUhnmRE4m9bgicq+4OArir7379LosOJt76xU/rVVwmHlckrWb5bWbqz8emKzcNOkVQQW\nqQgEAKBVUHYAAMB5UAluAtl4XOWjlS2fQdcmBYUNsqP9lWpAaxX2bFXQfgHVgB6pbv392ssjen0k\nVi4wWtkeTIaAUiUsjJMzG4JbOQSU3MtCnEGgJ63BaRWBs1oWMlHZl/vx92QGT0phTrZryZkQUKqE\nhVNbgZt8nTAjEACA1sc7DgAAzovKO/746Pclm8i0rahUAwZ5JadflB05KEnK9b6nmSeJBksmtrn+\n8Mi4XjhZUmcU6L9v6tCvbeiYdkxgjF4dLOuNsXhRbJN2tbwWPA4Co5RX2HUvC0kqv6HBgZcUHHlN\nNt+u8lvepXjr26YfEwQybwxIw4PN2xQ8FTMCAQBoeQSBAACcB8aEstaq/PrDkqSga6OCzotlx48q\nGXpZNokVdG9S0Ll+snoQ2Vet8Pu3g5VgZHVHoG3Lz7T/Vo8pJVZ/8tSgPvfTQT1/styck50FV0Wg\nKwhMrRjLmNTW4HorAicq/MLn90qSbHePkjUbKvdVA78gkOKy8g//g/KP/KPMwKF5nPECyaXMgGRG\nIAAALYN3HQAAnCfJ0CuVlt+oW2H3ZplcQcngS0qGK2/Yc703Vo9s3kmi4Y6Oxjo2VvmeHx1LtLF7\nYvGDzlQMvjYcqy00+tnxkn54pNisU62bKwjscFYE+rEsZN5BoCQNnZIZGpQkmeHTsit6K7dbO1kx\naE4el81FCl7vU3jgpXmc8QIJAudCGCoCAQBoHQSBAACcJ0F7r6INv6ncmh0KllyqZPy4klPPy8Zj\nCgoXKlyyRVKlehD+aM8ZVZfslhOrp4+XJFUqAasVg8+fKOn0RL/tlqWVoDBphdbPFK6Aq1CuDX+S\nfHvtgRmUS3mFPatlIVFeshO/sXGs4PD+ytdBMFkxGAwckhmrVNslq9ZW7k+a/MFCm+N7PEZFIAAA\nrYKtwQAAnCcm6lZuxdtlk7JMkJMdf0N24o19btUvSpKsjQkCPRMZM1kxNlK2euDFYZ0uJtqyNKd1\nXTn95GhR/3FoTCfGE61sD3Xd6ko7bdDCC0NK8fSEK7CJ2pJSzXHezAg07sTPNUsxVRBW/pFkSuPK\n/XCP4rFRJasulO1ZoeDgzxW+8FOZ0SHZziVKNl468bjmfs5v822aeaVSEQgAQOsgCAQAYIElQ/ul\nIC/TtlwmbJcJKj9uTcca5Xq3yy65VOHyqyq3EQJ6JbFW7Tmjd69u0yuny8oFRq+eLuur+4a1phDq\nRDHRqaLVyESJ3W9srCwRiROrMGjhIHBG7tUZu4Mff4JA9+3l2SwLifKKN12m4I3XpSBUcHxA5olH\nZZcukxkZlsaGZYqV9uvyFVefeVyTg0DnwpAiQSAAAK2CIBAAgAVgbSJjAsWn96l0cLdUHlJ4wbuV\nW7VdJlcJc0wQKVxyqWz3myYeY2VauMoLC69a1bf9wjb96GhRz5+oVM2dGE90YvxMuVgUGF2+LNKv\nbWifeFzjz3U2ijMqAjsd8wElyeb9mBGYS/l+1V0ROBHmxZe8WWHfywomFoGY0SGZ0aHJw2yQk129\nTvGbJ7YJt8DfJ9YR9hqWhQAA0DKYEQgAwAKobv0t9z8sO35cMqFMtHQyBJQqYWGlFTiYeEzz37Sj\ncabO+FvVEep/XNmt96x1z8z7xTVt+uhlnYoCo2QRBMblGQFXWhDoTUXgfGYETp3x171Upff8N8Vv\nusJ96CVbVbr2l6QwV3lcK1wnropAWoMBAGgZVAQCADBPk9WAp55TMtwnk2tXrvcG5S64tuaYZOSQ\nlOuWoiUtH+5gYVWrAY+MxsoHRr2FUJ+8slu3bOrQdw+P6/BwrAs7Q23szuldvXlFE2WArTwbsKo4\nY2twZ+J3EJhWEVjX1uBqa+/gKSnMyXb3qHTje1V+67UKX3pW5tRx2aXLlazoVXLxmyoh4NTHNZl1\nBIHMCAQAoHUQBAIAME/VCr/42BOVX+eXK+jaJOlM+68xgWxSVvHVB2WipYou/N9kui5u1imjQarf\n/1Ji9b9eL+qR18b0xniiN8YSXdaT0y+va9d1q9t0+5ZcTav4YmodrwkC0yoCXdViGZQ2I7CYGEmO\nskBrK9V8cVnBq/sUvvi0zPCQzPCgkt61ii97q5KNl6p89Q1njp352FZBRSAAAC2NIBAAgAVgiydl\ni6cmvj4l07Gmes9EoBPIjh+VCSIlQ68qPvWcAoLATKsGeYm1evClEf3TgdHJWXqBMfrx0aJ+fLSo\nbcsjffSyLm1empu2FGSxhIBS/a3BrvlxWZSbTWtwNchLEuWe/C+Fzz4pE5cr95lA4cFXFB58Rcma\nDSpde5PsytXTl4K02HXirghkRiAAAK2iNXoIAABY7IK8pIk0xJaVDL4iqVItWK0YTIYPyJZHKod3\nbqgcauvdHoDFplok9x+HxvTt/WdCwGo4WP362eMlPfDisIZKSUtvBj6bmRWBBc9nBM6qNXjiWgj3\n/VThM1NCQBlp8u8Ho6C/T7kffrdSXdcibcBOzq3B49NnHwIAgKaZ16uIwcFB3Xvvvbruuuu0du1a\nbdiwQTfeeKPuv/9+FYvFhTpHSdInP/lJ9fT0qKenR1dc4R6YDABA05icZEJJko3HVT78byq/8WMl\nY0clSfHpfYqP/VC2NCiTX6qwZ1vlYaaF39BjXqqh3tdfGVUpsVqaD/Sbmwu67ZKC3ndxhy7qrrQD\nS9JPjhW157A7PGt11tqagKsrdreC+tIaHBopdLQAOysCJ0K93E++L5OUZds7VX7rdSq//XqVr7ha\nybILVG0nDg/9XOHLPzuPZz5/Nl+7AMdYK5UW5/UNAEDWzLk1uK+vTzfffLP6+vokSYVCQePj49q7\nd6/27t2rb3zjG/r2t7+tnp6eeZ/kY489pq9+9avzfh4AAM4HaxOZMK+w50olI4clEyoZ7Zc9/K8y\nbStkS4NSeVh2IhzJrbp+4nGxzER4iGxJrFVgjB7rH9fR0VhL84E+sLmg/3ZxZYv06WKiq1aW9T9f\nHNYrpysVYC+dqvx7Mc0GlKSyI9xKXRbiSRAoVdqD4xkBaXFmUdxEi2/wyvMyw6crIeDbrlO87Z2V\n+8dGFazbqNwP9yh443VJUnC0X7HUerMBq1K+x2Z8TLatw3kfAABonDmVIcRxrFtvvVV9fX1avXq1\ndu/ercOHD6u/v19f+cpX1N3draefflp33HHHvE9wZGREn/jEJ5TL5XTVVVfN+/kAAFho1aq+cPlb\nFXRdJNlYkmRLg0qG9suOvyEbj8kEoYLuzQpXVrcJUw2YVdVNv3uPVTokwkC6tKfy+WtirZbkA739\ngrzu3Nql9rBybCJprLy4QkBJKiW1SWDqshBPWoMl98KQmorAiWrA8NDPJ35tlFxwYeXrJJHaO5Ss\n36zSu39ZNhdVbreJVCq2Zggo94xASSwMAQCgRczpHciDDz6o5557TpL0wAMP6IYbbqg8WRBo586d\nuu+++yRJDz30kPbs2TOvE/zsZz+rV199VXfddZcuu+yyeT0XAAALbeqMP5NfpuiiWxUuf5vz2GDZ\nWxWtvVkmyFWqCFv0jTzmz1qrxFrlJtqDj48l2j9YCYiNzoRnxkidUTDxGKk9bbhcCyvGtbf5vixE\ncs8JrJkRaK2UJLJBpTLYjAwpOF4ZJ1DdIjz5dbXl1kqK8uflnBdEakUgC0MAAGgFcwoCd+3aJUm6\n/vrrdfXVV9fcf8stt+iiiy6aduxc/OhHP9Jf//Vf65JLLtGnPvWpOT8PAADnS7Ua0BZPyJYGFbQt\nV/7iD6rt8v9LudU3KFx2hXKrb1R+44cUrd+poHDhtMchm4wxCqYsBQmM0T/uH9XjA+MyxiiaCAif\nfqOk8YklIr+wuhLuVB+zWJQd55taEehRa3Dk+CNeUxFoTKUqsPp7aAKFz/xQwav7KveFlSrS4PD+\nyVAw3jTxwXiLLt+gIhAAgNY26xmBIyMjeuKJJyRJO3bscB5jjNFNN92kL3/5y3r00UfndGLj4+P6\n+Mc/Lmut7rvvPrW31w4eBgCgGaoz3GxSVnLyWcXHn5QtnZYtnVJQuEjhyqsV9mxT0PGrNfPeFtv8\nN8xOnNhpm39/aW279hwe11hsdXCorD/6yWldsjSnbcsjHRqK9dzJskZKidZ35XRNbyVACRbZ9eGq\nCCw4ZgRaY2TDOY+nXnRcFYGTMwInZgNWxVuuUPjyszLlkoKTx5R/6JtKVq5Rsma9zMk3FAwckimO\nK+lZqeTiLZUHterm4LPMCAQAAM0361djL774opKJTyAvv/zy1OOq9w0MDOjEiRNatmzZrP47f/qn\nf6p9+/bp9ttv1/XXXz/b0wQA4LyYDAFtonL/fyg++n3Z5Ez7Xnx6n+LT+xR0b1K09mYFhbXTloIQ\nAmbP8bFYB4ZiXbUyPxkCxhOtv5uW5HTt6jY9+lolBDHG6OVTZb18qjxxHVl15wPdeklh8nFTg8TF\noFjnjMAkamvZuXbnw8wZgctLg7ro2BFJG8+EeBOvqe3KXiUbL1X40rMTRxsFx/oVHOtXpZncyrZ1\nqPz2XzjzuBYNAqkIBACgtc06COzv75/8es2aNanHTb2vv79/VkHgT3/6U33+85/XqlWr9Ad/8Aez\nPcUaY2PZeuFRLBan/RtIw7WCenCdzE411LPHf6Rk4L+kZKIcyqiy7WHi6+TUy4rj78is/4BM2CGp\n1KQzXhhcJ+n++tkRfW+gpM1LQv3GRW26blU07f7/Y3NOq6K8vjdQ0sHh6eVzPflA71uf09XL7OTr\nlcV2pQyP1pYEdsa1r72SKK9icbH9381dzuRU+Yuh4v987WG9f/hnCk+vUnHb1SpvvHTa8ePvfI/y\nnUsU/fwFBSffmHKPle0oaHzb1Sqt2yyNu9uuW0UoI9du4NLQaRWnvCbn7xTUi2sF9eA6QT2yfJ3M\npot21kHg0NDQ5NeFQiH1uKn3TX3MuZTLZX384x9XuVzWn/zJn6inp2e2p1jj8OHDimNH38oiNzAw\n0OxTwCLBtYJ6cJ3MzrJj/6ogGVYSdGi8/c2yJpRJxhWVDipXnngTP/6shosrNdZxZXNPdgFxnUw3\nVJYe6atUQD13VHru6IhW5K1+5YKyrl9+Zobb5ZLauwO9Fhm9NmY0MB5oa3esbV2JthirgwcrY+IW\nY8Fc37CRZkQ/rorAUpDTkaNHGnRWLSC+UFLl2lhSHtGNJ59THFrFr/UpfK1PttClU296i4YuPhMI\nBkt71XZxoPyp44oGTygaOqXRVWs1umqdxleskfr7W/5CaTt1Wksdt5/oP6zjBw/W3M7fKagX1wrq\nwXWCemTtOgnDUJs2bar7+JYb1HLffffpmWee0a/8yq/o/e9//4I854UXXrggz9MqisWiBgYG1Nvb\nq3y+hbfGoem4VlAPrpP6VTb9BrKnnlFyqiTlVii4YLu6Vlxbub88Io0ekj3ysOxopYK+vTCuYN36\nRT8bkOvE7Wcnytq4bExHx5LJTcBDkr55TPqPU0bv3dCmX1+f1/rQ6M2SxmKr9nDxXgcuJ4+XJZ2a\ndluXIwg07QWtumBVg86q+TqO5KSJgoOLx47qYNsKXZqcmByhl49LKrzwpOyrz6r45neouPXtUhRJ\nF2+SSiUpimQltU/8s1gEbe63Fys6C+pcv37y1/ydgnpxraAeXCeoB9dJxayDwK6ursmvR0ZGUo+b\net/Ux5zNCy+8oM997nPq6urSn/3Zn8321FJlddFIPp/P7P8bFhbXCurBdVK/4sB+KQhkwpzyPZsV\ntLdXQsL2dqlruZKOJSq+8mXZuKgwFyiKApkwGy82uE6me/MFVv93oV0vnCzph0eKevZEScWJLcDD\nsfS1V4v65oGSfv2idt2ysaCezjNz3UqJndwevJiZqLa9xrkspK1d+XxUc3tWTf3e7utYoz+66Dd0\nsw7pqo4XFfT3yUxsAVZpXB1PfV/tTz+h+M1vU/kt10pTXzvH5cntwYtCd7fz5igpS46/O/g7BfXi\nWkE9uE5QD9+vk1m/qpg5+2/btm3O4+qdJTjVpz71KRWLRd19993q6empaSmutvdaayfva2trUxT5\n86ISANA81lpJViao/Pi0pUElo/0KOjdIqmwRNkGu0rYXtktxJSDJSgiIWu05o81Lc9rQHerKFZFe\nOFnWj44W9dM3ShopVVqDS4nV7ldHtfvVUe1Y167f3FzQmkKYiRBQ0mQl5FTuGYEpSyQyKpqyy2M8\nzOvlwmrt6Vyh8hUbFAy8pqDvZQWH98sUK6GpScrKPfND5Z75oeJL36LyVdfJLlm2uEJAia3BAAC0\nuFm/stiyZYuCIFCSJHr++ee1Y8cO53HPP/+8JKm3t7fuRSEHDhyQJH3mM5/RZz7zmdTjDh06pHXr\n1kmS/uiP/ki//du/PZv/BQAA5qTS2mskm1RvUHzkezK5ToU92yRT+bGaDL4iJZWlCOGyynzAalsx\nsikKjNZ35bS2M9S25ZFePFnWj48VtfdYUSfHz8wKfOjQmB46NKZtyyN98spuXdAeLOqWcUkqOsYw\nu2YEpm6Tzaic49s6anKyy1YqXrpcyYUbZI4cVnjwFQWHXpUZHZ48Ltz3U4X7fqpkzQYVb3iv1LWk\npecCTpNL+eBjfLSx5wEAAJxmHQQWCgVdc801evzxx/Xwww/rE5/4RM0x1lo98sgjkqQbb7xx/mcJ\nAEATVTcFV4XL3674xFOycVHJ2BEVf/4/FRTWKujaJDt+RMnQAdl4TEH7KoVLt0oSIaAnAmO0phBq\nTSHUm5fn9O7evH58rKQfHy3qyJTtus8er7QQL/YQUJLK1lURWBsEJpFflbGR41tbqmbCQSC7ZJns\nkmVKVq9XsPEyBQd/rvDgKzJDZ+YtVluI7WK6ToJANsrLlKa3jFMRCABAa5hTr8Ftt92mxx9/XI89\n9piefPJJveMd75h2/+7du7V///7JY+v1zDPPnPX+3/qt39KuXbu0fv36cx4LAMB82NJpJaOvK1yy\nZTIEtLYS5JjChQqWvlnx8b2Vg41RMvKakpHXKlU71srkCsqtuWnycVODRPhhZXuole2hLu2JdG1v\nXnuPlbT3WFH7B8t6xwV5revKKbFWwWIKeRyqMxGn6nTMCPStNdhVEViq/a2SupYo6VqiZNVaJRu3\nKDj0auWf40cUr98s27NCShIpWEQfJuTbpBlBoAgCAQBoCXN6RfGhD31IW7dulbVWt99+u/bs2SNJ\nSpJEu3fv1l133SVJ2rFjh7Zv3z7tsffee696enrU09Mz2QoMAECrKR36joovf1nj++5XfOJpSZIx\nYeWfIK9o/U5FF/6ygo5eaWpFlLUyUZdyq29UuOwtk4+Dv3raAl21Mq//vqlDd27t0i2bCvrfL+ts\n9mktmGIy/deBTdQx0Ro/VeJZa3AU1KZ+M3+vpil0Klm3SeW3XqfSu39Z5be8S+V3/dL5O8HzyNUG\nTkUgAACtYU4VgblcTrt27dJ73/te9fX16X3ve58KhYKSJNHYWOWH/JVXXqkvfvGLC3qyAAA0gi0P\nKz7xU0lSMnxIxVcflDn8L8r13qjcymskVRaAhCuululYo2TksOzYgOzYUQVLtihYcpnC7k2V57LZ\naP/E/C3JB9q2PNAlS3JqnygXW+zVgJJUnrEspOBoC5Yk61lF4Flbg8+mvUN2zQaVV66Wqu3Ui6ka\nUHIvDGFGIAAALWHOa8guuugiff/739f999+v73znOzpw4ICiKNJll12mW265RXfeeafyeb9mwQAA\nsiEZHVDQfoFs8bhsMrGxfvyESn3fUvnwvym36nqFF/yCTNStcOlWBV2XpG4GJgTETO2untFFbGaV\nm2s+oERrsJTSGpxmEc9UpCIQAIDWNecgUJK6u7t1zz336J577qn7MXfffbfuvvvuOf33vvCFL+gL\nX/jCnB4LAEC9gsI6RRffpmS4T8mp55QM/Vw2KUuSbHlEpcP/rvLrDytceZ1yvdtlou7Jx9qkLBPM\n68crsKiUZlQEdsXuwMe/1uDa2+qqCMwCKgIBAGhZvFMBAGAGE+ZlCmtl2nsVdG9WMnxAyakXlAy+\nLDsRctgkVvnIYyofeUzhincot/o9CtpWEALCOzODQNeiEImKQEkqzqYicBGz+faa26gIBACgNfBu\nBQCAFCbIybSvkmlbqaBrk+zwQcWnX1Ay+JJsaWjyuPiNJxW/8aSC7k3KX/QBKeqhJRjemFnlltoa\n7FtFoOOvgNiaiU3RjT+fhnJWBBIEAgDQCggCAQA4B2MCmbYVUtsKBV0XKxm9UsnpfYpPvSBbPDl5\nXDJYaSHOwgIIoF6leEZFIMtCJEm5lP0epURqy/gicfeMQFqDAQBoBQSBAADMgsn3KMz3KCisV7D0\nzUoGX1Jy+kUlo68rXHppZcmITWTMItvyCczRzAUYaVuDfWsNdlUESpXfr8z/TrgqAovjkrUSH5QA\nALc/sbAAACAASURBVNBUBIEAAMyBiboVRt0KCmtll16u+NQLCpe/vdmnBTRccWZFYNqMwPzi3YI7\nFznjHgg4c8tyFjkrAq2thIFttfMDAQBA4xAEAgAwDybXKdO1SaZjnUxYCTqoBoRPapaFUBEoyb01\nWKqtoMyktHmQ42MEgQAANBnvVAAAWADVEBDwTd3LQnwLAtNag32oCEz5XjMnEACA5iMIBAAAwJwV\nayoC3dthXe2iWZZLCQJ9aA1Oqwg0bA4GAKDpCAIBAAAwZ+UZwVYXFYGS0luDyx60BqeGvlQEAgDQ\ndASBAAAAmLOZFYEFx7IQa4xsLmrUKbUErysCU+YAUhEIAEDzEQQCAABgzuqZEZhEbZJJScYyKnVG\noNcVgQSBAAA0G0EgAAAA5qx2a3Bt2OPbfEApvSLQh2UhYlkIAAAtiyAQAAAAc1YbBKZUBHomCtyl\nf1QEAgCAZiIIBAAAwJwV4+m/7nTMCPQyCPR5RiBbgwEAaFkEgQAAAJizuioC8/lGnU7L8Lk1mIpA\nAABaF0EgAAAA5mxmsFWgNViSFKW8yvahNTi9IpAZgQAANBtBIAAAAOasWEdFoPUxCPS5NThKqQCl\nIhAAgKYjCAQAAMCclWcEgV2OrcFeVgSmBIFlHyoCg0DWEQZSEQgAQPMRBAIAAGDOZla4OZeFpM2M\ny7C0GYFeVARK7vZgKgIBAGg6gkAAAADM2dRlIYFN1JGUao7xMQiMAnfpnxczAuVeGMLWYAAAmi/X\n7BMA0Hg2KSkZ2i8lxWafClqALRaVHz8ie3pI8Zh/mz1RH64TuJj8MpWSM58ruxaFSH7OCPR5a7Ck\nlIpAWoMBAGg2gkDAM+VjT2j8Z38ixSPNPhW0kJWSkiMStRo4G64TuHyha6NuHfwdHUuWOheFSMwI\nnMqXIJCKQAAAWhOtwYBHbDym8Z/dSwgIAFgwl+de1f+z7BuS3PMBJT9bg3Mpr7KLnrQGMyMQAIDW\nRBAIeCQ59Zzk2OYIAMB8/GLHzyTpLBWB/rWTUxFIRSAAAK2IIBDwiC2eavYpAAAyaHkwJMnSGjxF\nahBoU+7IGtf3vMiMQAAAmo0gEPCILQ81+xQAABmUM4k6zVhqEOiqDsu61NZgKgIBAEATsSwE8Eha\nEBht+ohM2NHgs0GrKJVLOnHipJYt61GUi5p9OmhRXCeoik/8VPGx/1Vz+9JgRJ0p4yd8rAhM3Rrs\n+4xAayXjSVUkAAAtiCAQ8IgtuYPAcOU1MgFv7H1VHh/X+OjrMj2rFbb592Yd9eE6QZWNR5xBYE8w\nwrKQKUIjBbJKND308mZGYFt7zW3GWqk4LjnuAwAAjUFrMOATV0VgkCcEBADUzYQF5+1LghFmBM4Q\nOV5p+xIEOisCJTYHAwDQZASBgEecrcEpb+gAAHDKuX9uLA2GCQJncLUHFz1pDbYp33MzzsIQAACa\niSAQ8IirNdikvKEDAMDF5Dqdt59tRqCPy0Ik9+bgsucVgSwMAQCguQgCAZ84KgIJAgEAs5KyXGrp\n2WYEUhE4yZuKQFqDAQBoSQSBgEdoDQYAzNfZKgILjtZgKyPr6aZp14zAou8VgUWCQAAAmokgEPCI\nKwhMe0MHAIBT2C6pttQtbUZgkm+TjKM0zgM+twanVwQyIxAAgGYiCAQ8YW0ilUdq78i5W7wAAHAx\nJnC2By9N2Rpso3wjTqsl+dwazIxAAABaE0Eg4IvysKTadx8mpCIQADA7rvmyS4MRdTmWhfg6H1CS\noqD2527J94rAMSoCAQBoJoJAwBPO+YBiWQgAYA5SgkDXspAk396IM2pJrorAkjcVge7vOxWBAAA0\nV67ZJwCgMdKCQJaFAABmy4SFmhrzJcGIOuLaY5O8v63BrhmB3lcEEgQCANBUBIGAL0pUBAIAFohj\n0dTSYFi5uPalpc+twc4ZgZ4EgekzAmkNBgCgmQgCAU+kVgSyNRgAMEtpMwIV14Y/1uMgMHIM4Sn7\n0hqctiSGikAAAJqKIBDwROqMQMfmRwAAzsY4xkp0BCUZx1IqKgKn86YiMAhko7xMqTjtZmYEAgDQ\nXCwLATxhU1qDqQgEAMxayliJQlisuS1JmxXnAeeMQF8qAiV3e3CRIBAAgGYiCAR8wdZgAMACcVUE\nSlJ7VKq5zeeKwCioTf18WRYiuReGMCMQAIDmIggEPGHLw45bAynw9w0aAGCOUj5EShxj4WzarDgP\neN0aLEmuEJjWYAAAmoogEPCELQ3W3pgryBjHuxQAAM7CpIyVsPnanym0Bk/nzbIQpVQEjlERCABA\nMxEEAr5wtAanvZEDAOBs0lqDXRWBSb79PJ9N68o5Xml7VRHYRkUgAACthiAQ8ISzNZiNwQCAuUhp\nDXZWBHrcGuz7shD3jECCQAAAmokgEPCELde2BlMRCACYi7RFU4mjAMznZSGuGYFla2R9CQNd3/si\nrcEAADQTQSDgCVtytQazMRgAMAcprcGuikBXVZgvopRX2r5UBVIRCABA6yEIBDxgrZWcrcEEgQCA\n2TNBTgpqW36dMwKpCKzhzZxAVwg8PiZ/SiIBAGg9BIGAD5JxyZZrbqYiEAAwZ47xEu4Zgf4GgZFx\nB15eVwRaK5WKTTgbAAAgEQQCfnBsDJaUOuwdAIBzcW0Odm8N9jgITGsN9rkiUJLGmRMIAECzEAQC\nPnC1Bcv9Jg4AgHq4qsqdMwI9rgj0vTU4bT4kcwIBAGgegkDAB7G7IpCtwQCAOXMEgUmbqzXYUSbo\niSglCPSlNTitItCMUREIAECzEAQCPkipCKQ1GAAwV66qcutsDW5vwNm0prSKQF9ag23a956KQAAA\nmoYgEPCApTUYALDQUlqD7ZTwy8rI5qIGnlRrSZ0R6HtFYJEgEACAZiEIBHzAshAAwAJL+zDJTsn9\nknybZFLK4jzAjECWhQAA0GoIAgEfpASBrkHvAADUI23O7NQ5gdbj+YBS+ozAsidBYGpFIK3BAAA0\nDUEg4IM4ZUYgrcEAgLnKdThvnlYR6PHGYEmKjLsHuOhJa3B6RSBBIAAAzUIQCPjANSMw7JAx/BUA\nAJgbE567IjBJC4I8kTojkIrABp8IAACoIgUAPGAdrcEsCgEAzEvKeImpm4N9rwhM3RrsSUVgWhDI\njEAAAJqHIBDwgas1mPmAAIB5SJszm+Snzgj0OwhMmxHo+7IQKgIBAGgegkDAB66KQIJAAMA8pG4N\nnloRmPd8WYjvrcFpQfAYFYEAADQLQSDgA+eMQIJAAMA81LE1OInaG3U2Lcn71uAgcG6OpiIQAIDm\nIQgEfOAIAqkIBADMS5BX2YY1N0+vCKQ12MWbikDJPSewSBAIAECzEAQCWWdjKal9wU0QCACYD2OM\nBm3tz5KpMwK9XxYSuEv/ir5UBMo9J9CwLAQAgKYhCAQyLkhG3HeE7pYuAADq5QoCp1YEutpCfUJF\noNxzAmkNBgCgaQgCgYwziftTdyoCAQDzNZicoyLQ89bg1BmBHgWB7opAgkAAAJqFIBDIuNSKQIJA\nAMA8nT5HRaDvrcGpW4M9ag12zggkCAQAoGkIAoGMSwsCDVuDAQDzdCqpHTMxfWuw50FgSkVg0fuK\nQGYEAgDQLASBQMYZm/Jim4pAAMA8nYw7am6zeclOfu13EJjaGmxT7sgiKgIBAGgpBIFAxqVWBBIE\nAgDm6aSjIlCBkc1VvvS+IjCtNZiKwCacCQAAkAgCgcxLbw1mazAAYH5OxO4PlapzAlkW4r69yIxA\nyfr0mwAAQOsgCAQyLkjZGkxrMABgPqxNDwKrm4N9rwgMjRSoNvAq+14RaK1UKjbhbAAAAEEgkHHG\nVRFoIpkgavzJAAAyI7YprcGS7ET243tFoOSuCvRpWYizIlCSKTInEACAZiAIBDLOWRFINSAAYJ5K\niXQqOXtFoPW8IlByzwksedQVm7YwxrAwBACApiAIBDLONSOQRSEAgPk6WxA4OSMwyjfwjFqTqyLQ\np2UhqRWBBIEAADQFQSCQccZREWhCgkAAwPyUrHQqpTV4ckYgrcGKXEEgFYG0BgMA0CQEgUDGObcG\n59gYDACYn+JZKwKNrIxsjopAV2swMwKpCAQAoFkIAoGMC6yjIjDX0YQzAQBkSSmRBhP3z5MkP9EW\nbBzlcJ7xvTU4dU4kFYEAADQFQSCQYdYmztZghVQEAgDmp5RIiQKdcoSBts0wH3CC763BqRWBYwSB\nAAA0A0EgkGXxiIxq322wLAQAMF/V9lbXnMAkz3zAqpyp/TnsU2uwbWt33s6MQAAAmoMgEMiy8rD7\ndoJAAMA8lSfCrNOuisC8UZLWEuoZ14zAMhWBzAgEAKBJCAKBLEsJAtkaDACYr3NWBBIESnLPCPSp\nIjA1CKQiEACApsjN58GDg4P6y7/8S/3TP/2TDhw4oDAMtXnzZu3cuVN33nmn8vnZz4Y5fPiw/uVf\n/kWPPfaYnn76afX390uSVq1apXe+8526/fbbtX379vmcNuCPeMh5s2FrMABgnqoLL07GtR8uMSPw\nDN9nBFoqAgEAaClzDgL7+vp08803q6+vT5JUKBQ0Pj6uvXv3au/evfrGN76hb3/72+rp6an7OQ8d\nOqQrrrhC1p55dVQoFGStVV9fn/r6+vTNb35TH/7wh/X5z39eYRjO9fQBP6S1BodsDQYAzE81CDxt\na4PAJKIisCrn6L/xaWuwUq4DgkAAAJpjTq3BcRzr1ltvVV9fn1avXq3du3fr8OHD6u/v11e+8hV1\nd3fr6aef1h133DHr57XWavv27frCF76g559/XocPH9Zrr72mH/zgB/q1X/s1SdLf/d3f6d57753L\nqQNesWUqAgEA50e1qu2UoyJQkVGcjxp7Qi3K94pABYFsznEt0BoMAEBTzCkIfPDBB/Xcc89Jkh54\n4AHdcMMNlScLAu3cuVP33XefJOmhhx7Snj176n7enp4effe739U//uM/6rbbbtOaNWsmn/eyyy7T\ngw8+qJtuukmS9Fd/9VcaG+MFBHBWLAsBAJwnpbPMCJSkpJ3ODckdBHo1I1ByzgmkIhAAgOaYUxC4\na9cuSdL111+vq6++uub+W265RRdddNG0Y+uxdOlSvfWtb0293xijD3/4w5KkoaEh7du3bzanDfgn\nZlkIAOD8KJ5la7AkJW3spJOkXFBb/udVa7DccwJNcbwJZwIAAGb9Cm1kZERPPPGEJGnHjh3OY4wx\nk5V7jz766DxOr1Zb25kXEkni2asoYLacrcGBFLY3/FQAANlSDbNGy+6lILbNUQrnIe9bg6WUisDR\nJpwIAACYdRD44osvTgZwl19+eepx1fsGBgZ04sSJOZ5ere9973uSpHw+r82bNy/Y8wKZ5AoCcwUZ\nw5szAMD8VIPAYtk9C5CKwIqcKwj07LNsm6/9AJLWYAAAmmPWW4P7+/snv67O8HOZel9/f7+WLVs2\n2/9Ujf379+tv//ZvJUnvf//7tWTJkroel7VZgsVicdq/gTRJcUg17z+Cdo2P046DM0ql0rR/Ay5c\nJ5hptBhKilQquWcBxmGsYpHrJbRG0vTfo1Iir34W53ORaq6SsUpFIK9ncS6890E9uE5QjyxfJ+3t\n9Xf9zToIHBo6U2FUKKTPGZt639THzNXo6Kg+8pGPaGRkRMuXL9fv//7v1/3Yw4cPK47jeZ9DqxkY\nGGj2KaDFrRw7oZkNW6Uk0vH+15tyPmhtx4690exTwCLAdYKqYye6Ja1QnBIEjttxHTl6pLEn1YJK\nYyskTa+aLCbS61M+XM+6yFrNrBtNRitzjHk9i3pxraAeXCeoR9aukzAMtWnTprqPn3UQ2Azlclkf\n/ehH9dRTTymKIn3pS1/ShRdeWPfjZ3PsYlAsFjUwMKDe3l7l8+65PIAklY/WftIRdSzVmjWrm3A2\naFWlUknHjr2hlStXKIrcLX4A1wlmKoxUAsC45G4BjjpzWnXBqkaeUktaMpKXBqffVpZR7+o18mVS\nR767tosnF5clidezOCfe+6AeXCeoB9dJxayDwK6ursmvR0ZGUo+bet/Ux8xWHMf62Mc+pn/+539W\nLpfTl770Jb3nPe+Z1XPMpkRyMcnn85n9f8PCGI5r/4yGUZfybbVDu4EoiqYtZAJcuE5QlVTzv5Tu\n3yCyyucJjfM5d1Aa5NuU92SMYtBe20VU3RrM61nUi2sF9eA6QT18v05m/fJj5uy/NPXOEjybagj4\nrW99S2EY6m/+5m/0vve9b07PBfjGWpu6LAQAgPkqT2y+zZfjM7+YKig39oRaVJTyaturhSHOrcFj\nkvVtfTIAAM036yBwy5YtCoLKw55//vnU46r39fb2zmlRSBzHuuOOO/TNb35zMgTcuXPnrJ8H8FYy\nLtnaN2GGIBAAsACKE0FWZzyuwDVzO2RRiCRFxh12FT3KwKwrCLSJTExYDABAo806CCwUCrrmmmsk\nSQ8//LDzGGutHnnkEUnSjTfeOOuTqoaAUysBb7nlllk/D+AzWx523xESBAIA5q80JQg0rlTLEARK\nUi5lDqBXFYGRe5xAUPRnczIAAK1iTpNJbrvtNknSY489pieffLLm/t27d2v//v3Tjq1XHMf66Ec/\nqm9961vK5XL64he/SAgIzEVp0HmzyXU2+EQAAFlUDbK64jEFjjzHGEIeidZgyV0RKBEEAgDQDHMK\nAj/0oQ9p69atstbq9ttv1549eyRJSZJo9+7duuuuuyRJO3bs0Pbt26c99t5771VPT496enp04MCB\naffFcaw777xT//AP/zC5GIR2YGBurGs+oMSMQADAgphsDU7cFYFGhDxSekWgT63BSlkwFJa4RgAA\naLRZbw2WpFwup127dum9732v+vr69L73vU+FQkFJkmhsbEySdOWVV+qLX/zirJ73Bz/4gf7+7/9e\nkmSM0ac//Wl9+tOfTj3+j//4jwkKgRRprcGG1mAAwAIon2NGoNFYY0+oRUUpQWCZikAFBIEAADTc\nnIJASbrooov0/e9/X/fff7++853v6MCBA4qiSJdddpluueUW3Xnnncrn87N6ziQ584qoVCrpyJEj\nZz1+dHR0TucO+MCmtgYTBAIA5q9aEVhImRFo7JhkE8nMqQElM9KCQK8qAlNbg11bZgAAwPk05yBQ\nkrq7u3XPPffonnvuqfsxd999t+6++27nfddff71Onjw5n1MCUEVrMADgPJq6LMQ5I1BWxo7KGr9n\n0+aYESibtiyEikAAABrO749ogQyjNRgAcD6Vps4ILLnL20xC90ZaRaBPQWBqRSBBIAAADUcQCGQU\ny0IAAOdTNftLqwiUJJOMNO6EWlRk3CFpSnaaTbQGAwDQMggCgaxyzQgM22VM2PhzAQBkztTWYNeM\nQIkgUJKilFfbRY8qAm2+3Xk7FYEAADQeQSCQUa7WYNqCAQALpTgZBI4pIAhMlUtrDaYikCAQAIAm\nIAgEMsrZGkxbMABggUyvCHQfExAEMiNQkk0JAsMiQSAAAI1GEAhklHW0BlMRCABYKFOXhQTjVASm\nSdsa7FNrMBWBAAC0DoJAIKtcW4OpCAQALJB6KgLZGpxeEVj2qTU4CGRzUe3NLAsBAKDhCAKBjHK1\nBhuCQADAApkWBJYlJbXJFhWB6TMCvaoIlJxVgVQEAgDQeASBQAbZpCzFjiqMsLPxJwMAyKRSIhmb\nqDMZl5GcVYHGEgRGgbv0z6tlIXLPCSQIBACg8QgCgSxytQWLikAAwMIpJlJHcib9c20OpiIwvTWY\nikBagwEAaAaCQCCDnBuDRRAIAFg4ZVtpC65yVQSyNTi9NdirGYGiIhAAgFZBEAhkUFoQKLYGAwAW\nSDGZHgS6NgdTEShFbA2uIAgEAKAlEAQCGWRLVAQCAM6vUnLuikC2BrMspMpZEUhrMAAADUcQCGRR\nWkUgQSAAYIGUEqkrHpv8deqMQOtZD+wMaTMCyzbljqyKaoPAkIpAAAAajiAQyKDUGYFsDQYALJBS\nInUm56gIVCxZv6u+qAissG3tNbcFRYJAAAAajSAQyCBagwEA51spkQpTZwQ6KgIl2oPTZgSWfCuU\nTJsR6HnFKAAAjUYQCGQRrcEAgPNs5rIQk1LcFSTDDTqj1hQayag27Cr5VhHoCAKNtVK51ISzAQDA\nXwSBQAY5W4NNTibIN/5kAACZEyeSlZm+NTitItD6XREouecEelcR6JgRKElmfMx5OwAAOD8IAoEM\ncgaBVAMCABZIdb7duWYEShMLQzznag/2bkagoyJQkkyRIBAAgEYiCAQyyDUj0IQEgQCAhVGtZqur\nIpAg0LkwpOxbRWBaEEhFIAAADUUQCGSRoyLQ5NgYDABYGNX5dtNmBFIRmMrVGkxFYAVBIAAAjUUQ\nCGSQuzW4o/EnAgDIpGqIVd/WYILAHK3BqRWBojUYAICGIggEMsjdGkxFIABgYZQnQqyu+EyIk1YR\nGBAEOisCaQ2uMOMskwEAoJEIAoGMsdZK5eHaO1gWAgBYIM5lIVYyjqpAkxD0uGYE+lYRmN4aPO68\nHQAAnB8EgUDWxCOSat9dGIJAA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      "text/plain": [
       "<matplotlib.figure.Figure at 0x202f2dc4710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(dpi=100)\n",
    "\n",
    "# PDF loc=0, scale=1\n",
    "plt.plot(np.linspace(-8, 8, 100), \n",
    "         stats.uniform.pdf(np.linspace(-8, 8, 100),loc=0, scale=1),\n",
    "        )\n",
    "plt.fill_between(np.linspace(-8, 8, 100),\n",
    "                 stats.uniform.pdf(np.linspace(-8, 8, 100),loc=0, scale=1),\n",
    "                 alpha=.15,\n",
    "                )\n",
    "\n",
    "# PDF loc=0, scale=2\n",
    "plt.plot(np.linspace(-8, 8, 100), \n",
    "         stats.uniform.pdf(np.linspace(-8, 8, 100), loc=0, scale=2),\n",
    "        )\n",
    "plt.fill_between(np.linspace(-8, 8, 100),\n",
    "                 stats.uniform.pdf(np.linspace(-8, 8, 100),loc=0, scale=2),\n",
    "                 alpha=.15,\n",
    "                )\n",
    "\n",
    "# PDF loc=-3, scale=3\n",
    "plt.plot(np.linspace(-8, 8, 100), \n",
    "         stats.uniform.pdf(np.linspace(-4, 4, 100), loc=-3, scale=3),\n",
    "        )\n",
    "plt.fill_between(np.linspace(-8, 8, 100),\n",
    "                 stats.uniform.pdf(np.linspace(-4, 4, 100),loc=-3, scale=3),\n",
    "                 alpha=.15,\n",
    "                )\n",
    "\n",
    "# LEGEND\n",
    "plt.text(x=-1, y=.65, s=\"loc=0, scale=1\", rotation=65, alpha=.75, weight=\"bold\", color=\"#008fd5\")\n",
    "plt.text(x=1, y=.65, s=\"loc=0, scale=2\", rotation=65, alpha=.75, weight=\"bold\", color=\"#fc4f30\")\n",
    "plt.text(x=-3, y=.65, s=\"loc=-3, scale=3\", rotation=65, alpha=.75, weight=\"bold\", color=\"#e5ae38\")\n",
    "\n",
    "\n",
    "# TICKS\n",
    "plt.tick_params(axis = 'both', which = 'major', labelsize = 18)\n",
    "plt.axhline(y = 0, color = 'black', linewidth = 1.3, alpha = .7)\n",
    "\n",
    "# TITLE, \n",
    "plt.text(x = -5, y = 1.1, s = \"Nniform Distribution - loc and scale\",\n",
    "               fontsize = 26, weight = 'bold', alpha = .75)"
   ]
  }
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